Using Predictive Modeling Algorithms for Non-Modeling Tasks - Machine Learning Times - machine learning & data science news
Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Re-examining Model Evaluation: The CRISP Approach
 The performance of prediction models can be judged using...
An Agile Approach to Data Science Product Development
 Introduction With the huge growth in machine learning over...
Wise Practitioner – Predictive Analytics Interview Series: Haig Nalbantian at Mercer – BIZ
 By: Eric Siegel, Founder, Predictive Analytics World for Business...
Is What You Did Ethical? Helping Students in Computational Disciplines to Think About Ethics
 In addition to this article, Dr. Priestly will also...
SHARE THIS:

6 years ago
Using Predictive Modeling Algorithms for Non-Modeling Tasks

 It is obvious what predictive modeling algorithms like decision trees, neural networks, linear and logistic regression, and others are used for: building predictive models for classification and/or regression. However, they can be useful for many other tasks in a predictive modeling project. Decision trees are particularly transparent models, which is one reason the are a favorite choice of practitioners when the models are used not only to provide predictions, but to explain patterns of behavior found in the data. Other algorithms, like neural networks, are often considered “black box” algorithms, meaning that they are more difficult to interpret due to

To view this content
Login OR subscribe for free

Already receive the Machine Learning Times emails?
The Machine Learning Times now requires legacy email subscribers to upgrade their subscription - one time only - in order to attain a password-protected login and gain complete access.

Click here to complete this one-time subscription upgrade

Existing Users Log In
   
New User Registration
*Required field

Comments are closed.

Pin It on Pinterest

Share This